Staff Software Engineer, ServiceNow
$176.1-308.2k
+ Variable/incentive compensation & ESPP
2 days a week in office (Santa Clara, CA)
Cloud-based digital workflows for enterprises
Be an early applicant
Cloud-based digital workflows for enterprises
1001+ employees
Be an early applicant
$176.1-308.2k
+ Variable/incentive compensation & ESPP
2 days a week in office (Santa Clara, CA)
1001+ employees
Company mission
To transform IT to revolutionize the enterprise.
Role
Who you are
- 8+ years of software development experience with a Bachelor's degree; OR 6+ years with a Master's degree; OR 3+ years with a PhD; OR equivalent work experience
- Practical software development experience, with 5+ years working with modern cloud-native and AI-native systems
- 3+ years of hands-on experience with LLM prompt engineering, agent design, and retrieval systems (RAG, semantic search, knowledge bases)
- 3+ years of demonstrated experience integrating third-party AI/ML services and platform APIs (OpenAI, Anthropic, AWS Bedrock, Google Vertex AI, etc.)
- 2+ years of hands-on experience developing applications and extensions on the ServiceNow platform
- Strong proficiency in JavaScript/GlideScript, Python, and Java; familiarity with ServiceNow scripting patterns and APIs
- Solid understanding of ServiceNow data model, form/workflow design, and business process automation
- Solid understanding of microservices architecture, REST/streaming APIs, and modern backend frameworks (Spring Boot, FastAPI, etc.)
- Experience designing and optimizing high-performance data pipelines, embedding systems, and vector stores at scale
- Demonstrated expertise in LLM orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel) and vector databases (Pinecone, Weaviate, pgvector, etc.)
- Experience with cloud computing platforms and managed AI services (AWS, GCP, Azure); hands-on experience with infrastructure-as-code
- Proficiency with Kubernetes, containerization, CI/CD pipelines, and automated testing frameworks
- Experience developing and debugging evaluation harnesses, benchmarks, and metrics for AI/ML features
- Proven ability to troubleshoot and isolate root causes in complex, distributed, and probabilistic systems
- Strong communication skills; ability to explain technical concepts to both technical and non-technical audiences; customer-facing experience a plus
- Experience with Agile and Scrum development methodologies; comfort with iterative development and continuous improvement
- Demonstrated ability to engage with customers, understand their needs, and support issue resolution
- Track record of taking ownership of significant technical initiatives and delivering them successfully
- Demonstrated mentorship of junior engineers or technical leadership in previous roles
What the job involves
- As a Staff Engineer, you will independently lead the design, development, and delivery of complex, high-impact AI-native and cloud-native systems. The IC4 engineer takes ownership of critical components or features, sets technical direction within their domain, and serves as a technical resource to peers and junior engineers
- They combine deep software engineering fundamentals with hands-on expertise in AI/ML integration, cloud architecture, and production systems. This role requires the ability to balance technical depth with organizational impact, working across teams to solve ambiguous problems and drive platform improvements
- Lead the design and architecture of complex, production-critical AI-native systems, including LLM integrations, agentic workflows, retrieval pipelines, and inference services
- Own end-to-end delivery of medium-to-large features or systems, including specification, design, implementation, testing, deployment, and production monitoring
- Make informed architectural and technical trade-off decisions between latency, cost, scalability, reliability, and model quality
- Establish evaluation frameworks, testing strategies, and production monitoring for AI-driven features; drive adoption of eval-driven development practices
- Design and optimize high-performance data pipelines, embedding systems, and vector stores handling millions of rows and complex retrieval scenarios
- Champion security best practices, including prompt-injection defense, data privacy, PII handling, responsible AI guardrails, and compliance with regulatory requirements
- Participate in architectural reviews across teams and contribute to platform-level technical decisions
- Stay current with emerging AI/ML frameworks, services, and techniques; evaluate and recommend adoption where applicable
- Mentor junior and mid-level engineers (IC2/IC3) through pair programming, design reviews, architecture discussions, and hands-on coaching
- Conduct thorough code reviews, including evaluation of prompts, agent logic, retrieval strategies, and AI/model behavior validation
- Identify technical debt and improvement opportunities; advocate for and lead initiatives to address them
- Share knowledge through documentation, brown-bag sessions, and architectural guidance
- Contribute to hiring and interview processes; provide technical assessment and feedback on engineering candidates
- Model best practices in software craftsmanship, testing discipline, and debugging methodology
- Support onboarding of new team members and ensure knowledge transfer across projects
- Work closely with product management, domain specialists, and other engineering teams to define requirements and technical specifications
- Translate complex technical concepts and AI trade-offs for non-technical stakeholders (product, leadership, customers)
- Lead root cause analysis for customer-reported issues, including those involving model behavior, hallucinations, retrieval quality, and distributed system complexity
- Participate in design reviews, technical planning sessions, and retrospectives; contribute perspectives on technical feasibility and risk
- Communicate clearly about design decisions, implementation challenges, AI limitations, and production incidents
- Build and maintain relationships with adjacent teams and external partners where applicable
- Proactively identify opportunities to improve development processes, tooling, and team efficiency
- Develop robust, maintainable, and well-tested AI-native software using Python, Java, and JavaScript as appropriate
- Build comprehensive unit tests, integration tests, and AI evaluation harnesses (accuracy, regression, hallucination detection)
- Troubleshoot complex issues in distributed systems, probabilistic models, and cloud infrastructure; isolate root causes efficiently
- Implement secure coding practices and responsible AI guardrails throughout the development lifecycle
- Manage deployment, monitoring, and iteration of features in production; respond to performance issues and model drift
- Work with cloud services (AWS/GCP/Azure), managed AI services (Bedrock, Vertex AI, Azure OpenAI), Kubernetes, and CI/CD pipelines
- Contribute to code and architecture standards; ensure adherence to established best practices
- Design and develop custom applications, extensions, and integrations on the ServiceNow platform
- Develop workflows, business rules, and automation using ServiceNow scripting (JavaScript, GlideScript, REST APIs)
- Build data models, forms, and dashboards for ServiceNow applications; optimize database queries for performance
- Integrate third-party AI/ML services and custom APIs with ServiceNow platform services
- Contribute to and maintain ServiceNow plugin and app architecture; follow ServiceNow best practices and coding standards
- Participate in ServiceNow upgrades and configuration management; ensure compatibility with platform updates
- Mentor junior engineers on ServiceNow platform capabilities and development patterns
- Participate in customer issue triage and root cause analysis for production ServiceNow application issues
- Work closely with customer success and support teams to understand and resolve complex technical issues
- Provide technical guidance to customers on application usage, configuration, and troubleshooting
- Identify patterns in customer issues and drive improvements to prevent recurrence
- Contribute to customer documentation and internal knowledge bases
- Support customer escalations; provide timely resolutions to critical issues affecting customer operations
- Gather customer feedback and communicate product improvement opportunities back to product management
Our take
ServiceNow provides cloud-based solutions that define, structure, manage, and automate services for enterprise operations, transforming old, manual ways of working into modern digital workflows. The company was founded in 2004 with a vision to build a cloud-based platform that would enable regular people to route work effectively through the enterprise.
Much as Salesforce enables a company to manage its external clients by keeping a record of all contacts and interactions, ServiceNow promises an internal system to meet the needs of employees. It has succeeded in claiming half the market, setting itself apart from legacy IT service-management software players like BMC Software, Hewlett Packard Enterprise, Cherwell Software and CA Technologies.
The company's success comes from two product traits: simplicity and customisability. ServiceNow's IT tools don't require the IT department to set them up. Once running, they offer a single collection centre for requests, data points and checklists, all of which can in turn be analysed by algorithms to predict needs, flag concerns and measure efficiency.
The company has more than 7,700 customers, including 85% of the Fortune 500 list of the United States' largest corporations. ServiceNow now looks to increase its revenue threefold in the upcoming years and has entered into a 5-year partnership plan with Visa, beginning with the launch of a Visa-integrated dispute resolution solution for issuers. The company is prioritising organic growth over mergers and acquisitions, with a target revenue of $15B, something which its Visa partnership will no doubt aid in achieving.
Freddie
Company Specialist at Welcome to the Jungle
Insights
16% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Mar 2012
$11m
GROWTH EQUITY VC
Feb 2012
$17.9m
GROWTH EQUITY VC
Total funding: $83.8m
Company benefits
- Generous family leave
- Matched donations
- Annual learning stipends
- Flexible PTO
- Competitive retirement plan
- Paid volunteer time
Company HQ
Santa Clara, CA
Salary benchmarks
We don't have enough data yet to provide salary benchmarks for this role.
Submit your salary to help other candidates with crowdsourced salary estimates.
Share this job
View 196 more jobs at ServiceNow